Power systems are designed to be able to adjust to various disturbances such as faults, large changes in loads or loss of generation and continue to operate satisfactorily within the desired bounds of voltage and frequency [1]. However, they are not designed to be immune to all possible events; unexpected events can happen in the system leading to rotor angle, frequency or voltage instability [2]. The rotor angle instability may be initiated either by a small disturbance to the system such as a change in load or a large disturbance such as a fault in the system. The large disturbance rotor angle instability (which is also commonly referred to as transient instability) usually appears as aperiodic angular separation due to insufficient synchronizing torque, manifesting as the first swing instability. However, in large power systems it is also possible that the transient instability occurs in the later swings, mainly related to a lack of sufficient damping torque [3] [4].
Protection against rotor angle instability or loss of synchronism, which is also referred to as out-of-step protection is often provided using distance relays [5]. Effectiveness of such local measurement based out-of-step protection systems is limited in minimizing the effects of system wide disturbances [1]. In order to overcome these disadvantages, several utilities have developed wide area protection schemes referred to as special protection systems (SPSs) or remedial action schemes (RASs). These systems are mostly event based systems designed to directly detect selected outages that would lead to instability using binary (transfer trip) signals and take predetermined corrective actions [5]-[7]. This method has been adopted mainly because of the very short response time required for avoiding transient instability [6]. However, implementation of event based special protection systems can be extremely complex, cumbersome and expensive [6], [7]; this is because a large number of tele-protection systems are needed to convey all relevant system contingencies to the stations that must execute corrective actions. They need to be continuously armed and de-armed with the changing system conditions [5].
In contrast, response based wide area protection and control systems employ strategically placed sensors, such as phasor measurement units (PMUs), that react to the power system response to arbitrary disturbances [6]-[7]. Managing of such systems is much simpler than comparable event based systems. The capabilities of PMU technology, telecommunications and real-time data processing are approaching a level that is acceptable for implementing response based protection and control against large disturbance rotor angle instability; generally a response time of the order of 1 s is required [6].
In one of the earliest schemes of wide area measurements based out-of-step protection, Tokyo Electric Power Co. (TEPCO) used the measured phase angle difference between two groups of generators to predict the future phase angle difference values and perform controlled system separation if the predicted phase difference exceeds a threshold [10]. The Western Area stability and voltage Control System (WACS) implemented on the Bonneville Power Administration (BPA) system uses the time integral of the weighted average of 12 voltage magnitude measurements on the 500 kV network as a measure of instability. Control actions such as capacitor or reactor bank switching and generator tripping are activated when this integral exceeds certain preset thresholds [7]. An alternative algorithm of the same system uses generator reactive power measurements as additional inputs to the controller and uses a fuzzy logic system to determine final control actions [7].
Some recent studies have shown that machine learning techniques can be applied to rotor angle instability protection problems [4][7 ][11][12]. In [11], the oscillations seen after clearing a severe fault are represented using an autoregressive model for which the input is the voltage phase differences between substations. The stability status of the system is determined by analyzing the roots of the pulse transfer function of the online identified autoregressive model. An array of neural networks (NNs) was used in [4] to predict unstable oscillations between groups of two generators. These NNs take phase angle difference between the two generator buses and its rate of change as inputs. The outputs of the NNs are processed through a voting procedure to determine the transient stability status of the system. Despite the limited success of these schemes, systematic approaches for designing wide area protection and control systems against the large disturbance rotor angle instability is a necessity.